Ashley D. Spear

Reconstructed and analyzed X-ray computed tomography data of investment-cast and additive-manufactured aluminum foam for visualizing ligament failure mechanisms and regions of contact during a compression test

Three stochastic open-cell aluminum foam samples were incrementally compressed and imaged using X-ray Computed Tomography (CT). One of the samples was created using conventional investment casting methods and the other two were replicas of the same foam that were made using laser powder bed fusion. The reconstructed CT data were then examined in Paraview to identify and highlight the types of failure of individual ligaments. The accompanying sets of Paraview state files and STL files highlight the different ligament failure modes incrementally during compression for each foam. Ligament failure was classified as either “Fracture” (red) or “Collapse” (blue). Also, regions of neighboring ligaments that came into contact that were not originally touching were colored yellow. For further interpretation and discussion of the data, please refer to Matheson et al. (2017) [1].

Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

A surrogate model methodology is described for predicting in real time the residual strength of flight structures with discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. A residual strength test of a metallic, integrally-stiffened panel is simulated to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data would, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high-fidelity fracture simulation framework provide useful tools for adaptive flight technology.